[1]Yang Zhongming,Plum Dragon,Hu Yinwen,et al.A Pedestrian Pattern Recognition Detection Algorithm Based on Foreground Extraction[J].Journal of Zhengzhou University (Engineering Science),2019,40(05):91-96.[doi:10.13705/j.issn.1671-6833.2019.02.017]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40卷
Number of periods:
2019 05
Page number:
91-96
Column:
Public date:
2019-10-23
- Title:
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A Pedestrian Pattern Recognition Detection Algorithm Based on Foreground Extraction
- Author(s):
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Yang Zhongming 1; Plum Dragon 2; Hu Yinwen 2; Huang Han 2; Cai Zhaoquan 3
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1. School of Computer Engineering Technology, Guangdong Vocational College of Science and Technology; 2. School of Software, South China University of Technology; 3. Huizhou University
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- Keywords:
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background modeling; pedestrian detection; face detection; AdaBoost; model recognition
- CLC:
-
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- DOI:
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10.13705/j.issn.1671-6833.2019.02.017
- Abstract:
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In this paper, the algorithm principles of Gaussian mixture model, HOG+SVM classifier and Haar+ Adaboost classifier were exploved. A pedestrian detection algorithm based on foreground extraction and pattern recognition was proposed. The background modelling was executed by using Gaussian mixture model and then the moving object was entracted by using foreground modeling methods. The pedestrian detection hased on the moving objects and face recognition on the objects were execnted. By this, the misjudgment problems was solved based on background modeling methods and efficiency problems based on statistical learning methods. The experimental results showed that the new algorithm could greatly reduce the missed detection rate compared to using the pattern recognition algorithm alone, and it performed well in terms of running speed and detection rate.